a multi-rheologyice model: segment-ice · 2011. 2. 2. · ren, d. et al. (2010), greenland ice...
TRANSCRIPT
Pictures adapted from R.Bindschadler (NASA GSFC) (L) and Ginny Catania
(UTIG) (R)
A Multi-Rheology Ice Model: SEGMENT-iceFormulation and Application to the Greenland Ice Sheet
Diandong Ren, Rong Fu, Lance M. Leslie
Jackson School, UT Austin & ASDI, Curtin, AustraliaLand Ice Working Group Meeting
Boulder, Colorado. January 12-13, 2001.
Review of previous studies
Reactions of the Greenland ice sheet to climate changes have already been investigated by Kuhn (1981) and Ambach (1985) as sensitivity studies
Huybrechts et al. (1991), van de Wal and Oerlemans (1997), and Greve (2000)
Ohmura et al. (1996) using a general circulation model (GCM) provided forcing series of temp. & precip. rate
van der Wal and Oerlemans (1994) suggests a net melting of 0.52 cm yr-1. In contrast, Huybrechts (1994) gives a thickening at a rate of ~ 1cm yr-1, while Ohmura et al. (1996) gives yet another picture. Although the latter’s estimate of precipitation is about 25% above observational estimates, its conclusions are echoed recently by Meier et al. (2007)
Observational research: Zwally et al. (1990) , Douglas et al. (1990) ; Rignot & Kanagaratnam, 2006; Ashcraft and Long (2006); Mote (2007)
It would be ideal to study this issue in a fully coupled modeling system. Unfortunately, few present coupled ocean-atmosphere climate models (CGCMs) include the interactive land ice flow dynamics (R. Binschandler, personal communication, 2006; M. Openheimer, personal communication, 2007)
The IPCC AR4 (http://ipcc-wg1.ucar.edu/wg1/wg1-report.html) used only a surface-mass-balance estimation in sea-level predictions, stating that “quantitative projections of how much the accelerated ice flow would add (to sea level rise) cannot be made with confidence, owing to limited understanding of the relevant processes (FAQ 5.1).”
Sea level rise andGrIS related recent publications
Alley, R. (1993), In search of ice-stream sticky spots. J. Glaciol., 39, 447-454.
Alley, R. (2000), Ice-core evidence of abrupt climate changes. PNAS, 97, 1331–1334.
Alley, R., T. Dupont, B. Parizek, S. Anandakrishnan, D. Lawson, G. Larson, and E. Evenson (2005), Outburst flooding and initiation of ice-stream surges in response
to climatic cooling: A hypothesis. Geomorphology, doi 10.1016.
Shepherd, A.,and D. Wingham, 2007: Recent Sea-Level Contributions of the Antarctic and Greenland Ice Sheets. Science , Vol. 315 no. 5818 pp. 1529-
1532
Bueler, E., and J. Brown (2009), Shallow shelf approximation as a “sliding law” in a thermomechanically coupled ice sheet model. J. Geophys. Res., 114, F03008.
Hooke, R., 1981: Flow law for polycrystalline ice in glaciers: comparison of theoretical predictions, laboratory data, and field measurements. Rev. Geophys. Space
Phys. 19, 664-672.
IPCC, AR4 (2007), Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental
Panel on Climate Change. Solomon, S., D. Qin, M. Manning (eds).
Landerer, F., Jungclaus, J., and J. Marotzke (2007), J. Phys. Oceanogr. 37, 296-312.
MacAyeal, D. (1992), Irregular oscillations of the west Antarctic ice sheet. Nature, 359, 29-32.
Meehl, G.A., et al. (2007), Global Climate Projections. In: Climate, Change 2007: The Physical Science Basis. Cambridge University Press, Cambridge, UK and NY,
USA. Projections of Global Average Sea Level Change for the 21st Century Chapter 10, p 820.
Mernild, S., G. Liston, C. Hiemstra, J. Christensen (2010), Greenland Ice Sheet Surface Mass-Balance Modeling in a 131-Yr Perspective, 1950–2080. Journal of
Hydrometeorology, 11, 3-25.
Paterson, W. The Physics of Glaciers, 3rd ed., 481 pp., Butterworth-Heinemann, Oxford, England (1994).
Peltier, W. R. in Sea Level Rise: History and Consequences (eds Douglas, B. C., Kearney, M. S. & Leatherman, S. P.) 65-95 (Academic, 2001).
Rahmstorf, S. (2007), A semi-empirical approach to projecting future sea-level rise. Science, 315,368-370.
Raper, S., and R. Braithwaite (2006), Low sea level rise projections from mountain glaciers and icecaps under global warming. Nature, 439, 311-313.
Ren, D. et al. (2010), Greenland Ice Sheet Response to Transient Climate Change simulated by a new ice sheet dynamics model. J. Geophys. Res-Atmos. (Accepted)
Rignot, E., and P. Kanagaratnam (2006), Changes in the velocity structure of the Greenland ice sheet. Science, 311, 986-990.
Van den Broeke, M., J. Bamber, J. Ettema, E. Rignot, E. Schrama, W. van de Berg, E. van Meijgaard, I. Velicogna, B. Wouters (2009), Partitioning recent Greenland
mass loss. Science, 326, 984-986.
Van der Veen, C. (1999), Fundamentals of glacier dynamics. A.A. Balkema, Rotterdam, Netherlands, 472pp.
Wang, W., R. Warner (1999), Modelling of anisotropic ice flow in Law Dome, East Antarctica. Annals of Glaciology, 29, 184-190.
Yin, J., M. Schlesinger, and R. Stouffer (2009), Model projections of rapid sea-level rise on the northeast coast of the United States. Nature-geosciences, 2, 262-266.
Zwally, H., and M. Giovinetto (2001), Balance mass flux and ice velocity across the equilibrium line in drainage systems of Greenland. J. Geophys. Res. 106, 33717-
33728.
Zwinger, T., R. Greve, O. Gagliardini, T. Shiraiwa, and M. Lyly (2007), A full Stokes flow thermo-mechanical model for firn and ice applied to Gorshkov crater
glacier, Kamchatka, Ann. Glaciol., 45, 29 – 37.
GRACE ICESat
-100 Gt per year -80 Gt per year
Greenland Ice Sheet Mass Balance
Greenland Ice Sheet = 5 m sea level equivalent
Increased surface melt
Arctic Climate Impact Assessment
2002
R. Braithwaite
1992
G. Catania
Vanity Fair 2006
3m sea-level rise
Accumulation area Ablation zone
• Surface melt water lubricating
effect (H. Zwally et al., 2002)
• Granular (basal tillage) basal
sliding effect ―“graded
glacier” concept (R. Alley 2005)
Lubricant at interfaceGeothermal heat flux
Rnet, LE, H
Flow in the Greenland ice sheet
Bedrock
silt
air
Bedrock
ice
(A)
(C)
(B)
Bedrock
Ice outspread
Silt loss
Melt
Water
drainage
Three stages of a mountain glacier
snout movement
Governing equations for ice flow
,,,),(2
1rji
x
u
x
u
i
j
j
iij
2)(2
1
tre
(1)
(2)
(3)
(4)
(5)
(6)
Ren et al. 2010a: A Multi-Rheology Ice Model:
Formulation and Application to the Greenland Ice
Sheet. JGR. In Press.
Ren et al. 2010b: The Greenland Ice Sheet
Response to Transient Climate Change. J.
Climate. Under Review. 2 2 2 2 2 2 22 2( )eff xx yy zz xy xz yz (7)
2
12
eff
p
TV T T E
t C
Ren’s contact :
[email protected]; [email protected]
111
)(),,(
ne
nAPT
Selection of coordinate system (always in rotating earth ref. sys.)
Y
X
Z
O
r
Lame operators:
00
00
00
00
00
sin ; cos
; ; ; sin
cos ; ;1
r
rr
rHrHH r
0
0 0r
General curvilinear system:Sacrifying the orthogonality in r-direction, introduce the terrain
following system:
ice
),( h
r
H
rhs
Where h is surface topography, H is local thickness,
and r is vertical coordinate
The old (spherical) to new (terrain following,
calculation space) coordinates transformation Ja (1st
order) and He (2nd and higher order) are:
,,
,,,
,,,
1
1
r
FH
s
F
ss
F
H
FF
ss
F
H
FF
rs
rs
),( H
Specific to Greenland ice sheet
nz)/2(1a where
nz/2, ... 1,2,ifor )1(1
2tanh
)2tanh(
min
a
a
mmi
Vertical stretching using hyperbolic tangent function:
Basal treatment for water terminated glaciers (ice shelf/ocean interaction)
Elevated thermal
forcing:
0ln
)1ln(*
STc
sTRT
p
freeze
Turbulent heat transfer:
DH
p
C
sm
kgKJc
mkg
coef.transfer
eddy dependent stability
and;108.1
viscositykinematic
;//3986
;/1028
127
3
Ca2+
SO42-Cl-
Mg2+
Na+
Electrolytes considered:
Sodium, chlorine,
magnesium, sulfur & calcium
......
0
*
*
**
...
0
0
0
z
zbyy
zaxx
ybxaz
z
y
x
Forw
rad m
odel
Invers
e m
odel
Data
assim
ilatio
n
Usages: uncertain parameter retrieval; initial states (historical residual
effects); and sensitivity experiments
Inverse modeling of SEGMENT-ice:adjointbased optimization
Ice Physics in SEGMENT-iceEffects of temperature and strainstage
Further, in SEGMENT-ice, flow-induced anisotropy also is considered,
following Wang and Werner (1999)
Effects of granular layer
Flow speed profile for an idealized geometry: -10 °C ice of uniform 30 m thickness resting on a
slope of 2 degrees steepness, 45 degree aspect (facing due northeast), and infinite length and
width. Comparison between the case with an underlain granular layer of 2 m deep, with grain
effective radius 10 cm, density of 2.7×103 kg m-3, and 30 degree dry repose angle (hatched) and
the case without such a granular base. Free-of-stress upper boundary condition is applied. The
inset is a zoomed-in of the velocity profile within the granular basal layer.
Dilatant granular layer
enhances the overlain
ice flow speed!
• MIROC-hires simulated spatially
averaged surface air temperature (a
& c) and precipitation rate (b & d)
trends over GRL
Decadal survey period 21-year low-pass filtered
• The annual mean temperature (c)
increases by ~4 °C over the next
century. Mean while, the annual
mean precipitation (d) increases
by 0.3 mm/day
• Without robust long-term modeling
estimations, it thus is unclear
whether GRL loses mass due to
climate warming
• During the surveyed period (confined
by the vertical grey lines), both
temperature and precipitation trends
are large within the 20th century but
are modest when compared with the
future ~100 years
Climate is warming up
Center for Climate System research, University of
Tokyo; NIES; Frontier Research Center for Global
Change
Modeling of Greenland Ice Sheet
Accurate prediction of future sea level rise requires
In2010, the Greenland Ice Sheet already is contributing 0.7-0.8 mm/yr sea level rise (E. Rignot, personal communication), to estimate the future contribution of GrIS to sea level under a constant warming climate, we need models that have the ability to reproduce/explain its recent observed dramatic behaviour
This study presents a new multi-phase, multiple-rheology, scalable and extensible geofluid model of the Greenland ice sheet that shows the credential of successful reproducing the mass loss rate derived from the Gravity Recovery and Climate Experiment (GRACE), InSAR observed surface ice flow speed, and the microwave remote sensed surface melt area over the past decade
Projections for the upcoming 50/100 years are made for each metric discused
Modeling of flow fields
U-comp V-comp W-comp
(a) (b) (C)
Modeling of flow fields
N S
N
S
sfc
btm
Modeling of flow fields 1
2
The surface velocity fields at present as measured by InSAR (a)
(http://websrv.cs.umt.edu/isis/index.php/Present_Day_Greenland), simulated by
PISM (b) and SEGMENT-ice (c). Ice sectors are clearly identifiable from flow
patterns. In plotting the vector field, the data have been thinned for clarity by
displaying one in every twenty grids eight data grids.
Modeling of flow fields
Region-by-region comparisons between SEGMENT-ice and InSAR observations of the
present surface velocity fields. The observed velocity field (a) is representative of the early
21st century speeds. The SAR data were provided by the Canadian Space Agency and then
processed by the NASA-funded Alaska SAR facility. (b) a region-by region scatter plot of the
u-component; and (c) for the v-component.
Modeling of Greenland Ice Sheet Mass LossGLAS instrument on the Ice,
Cloud, and land Elevation Satellite
level IIaltimetry data
(Zwally et al. 2003)A subset of these data is used from samples
that are not contaminated by thick clouds, wet
snow surface, and instrument problems. First,
we average the pixels of years 2003 and 2007
into 5-km boxes and then compare the maps
from these two years to determine ice sheet
elevation changes.
Future projections
CCSM MIROC-hires
Future projections
Net mass balance of the GrIS for the 20th and 21st centuries. Comparisons are among
using two CGCM provided meteorological conditions: MIROC3.2-hires (dot line) and CCSM3
(blue solid line), NCEP reanalysis provided meteorological conditions, and GRACE
observations (red dashed line).
The inset is a zoom-in for the past decade. Comparisons are between model simulation
using NCEP reanalysis provided meteorological conditions (black line) and GRACE
measurements (red line).
Because GRACE mts are only meaningful as relative values compared with the starting
point, we shifted the curve so that the two curves have the same value at the first mts time.
Mass loss rate: -160 km3/yr
GRACE: -147 km3/yr
•Microwave mts. obtain good
estimation of the ice sheet sfc. melt
extent and duration because Tb and
σ0 both are sensitive to liquid water
present in snow (Ashcraft and Long
2006)
• Observed (upper panels) and
simulated (lower panels) SME
(melting areas are in red)
• ‘near-surface forcing criteria’ for
surface melting is stipulated as a T2m
> -5 °C& Rnet > 170 W m-2
(L.Thompson, May 2007, personal
communication)
• The model simulated yr 2002 melting
extent (c) is very close to that
observed (b)
• Panels (a) and (b) are adapted from
Chapter 6 in ACIA2005, and
originally from K. Steffen,
CIRES/U. Colorado at Boulder
MIROC-hires
Summer maximum surface melt extent (SME)
OBS OBS
Total SME time series
The seasonal surface melt extent on the
Greenland ice sheet has been observed
by satellites since 1979 and shows an
increasing trend
Obs. re-procesed based on National
Snow and Ice Data Center (NSIDC)
archive of Tb at 25 km reso. on a NPS
progection. See total ice cover of ~1.7
million km2 close to what the model see
Different definition of surface melt may
account for the differences in magnitude
•There are no permanently frozen
surfaces south of 68°N
•South of 75°N, the melting expands
inland and approaches the 2500 m
elevation contour, while on the colder
northern side it generally reaches the
2000 m contour
•Centred on the intersection of the
74°N and 38°W, the melt area
increases steadily after 2020 and
extends to ~1×106 km2 by 2100, with
the melting front surpassing the 2600 m
elevation contour, leaving only ~7×105
km2 of frozen surface area surrounding
the Summit
• The two CGCMs project a very similar
pattern for increased SME
Maximum SME projection
CCSM3
Miroc-hi
Future projections
Surface ice temperature changes 2000-
2100 simulated by SEGMENT-ice, driven
by the NCAR-CCSM3 (B1) scenario for
meteorological forcing.
Cooling areas at lower elevations exist,
especially in the north; likely due to
horizontal advection of inland, colder ice.
Because ice temperatures are higher at
these lower elevations, the ice flow is large
and horizontal advection dominates other
heating (e.g., sensible heat flux and
precipitation).
In the vast central GrIS, horizontal
advection (a cooling effect) is relatively
small and sensible heat flux warming
dominates.
In between is a ring with greatest
warming, corresponding with strong
precipitation input, which usually heats the
ice.
Ren et al., 2010: A new ice sheet model –formulation
and verification